Abstract: Acquisition of evidence-based understanding of human health behavior and exposure to environments forms a central focus of health research, and a critical prerequisite for effective health policy. The use of mobile devices to study health behavior via cross-linked sensor data and on-device self-reporting and crowdsourcing offer compelling advantages to complement traditional techniques. Data collected on such devices can be particularly powerful in supporting understanding of health behaviors in areas where accurate self-reporting is difficult, including nutritional intake, physical activity and sedentary behaviour, and exposures to physical and social environments. Through structured surveys and crowdsourcing mechanisms, such devices can further provide potent means of gaining insight into knowledge, attitudes, beliefs, and perceptions in health areas. Finally, while little explored, some of the most powerful uses of such day lie in terms of understanding the particular causal pathways impacted by interventions. This hands-on talk will provide public health researchers and practitioners with a high-level introduction to the motivation, state-of-the-art in and tools for use of mobile data collection in public health. Topics touched on include elements of motivation, study design, behavioral ethics concerns and needs, data collection systems requiring low technical involvement, and analysis. Participants will be invited to experience a state-of-the-art and widely used mobile data collection system during the talk that illustrates many of the principles discussed.
Sponsored by The Department of Community Health Sciences along with the Center for Social Statistics and the California Center for Population Research